Data Science Master’s Programs

Data science is best taught at the master's level – an example of a master's degree in data science is our partner UC Berkeley's Master of Information and Data Science (MIDS) program – as it requires proficiency in multiple disciplines, including advanced statistics, computer science, applied mathematics, data analysis, and business analytics. Developing a holistic approach that taps into all of these disciplines is the ultimate goal of any quality graduate program in data science.

Our partner the UC Berkeley School of Information offers a professional Master of Information and Data Science (MIDS) delivered online. The program is accredited by the Western Association of Schools & Colleges (WASC), and is designed for professionals seeking to solve real-world problems by utilizing complex data from clickstreams, transactions, archives, sensors, and more. In this program, students will be prepared to apply disciplined, creative methods to define a research question; to gather, store, retrieve, and analyze data; to interpret results; and to convey findings effectively. The curriculum will introduce the latest tools and methods for identifying patterns and gaining insights from data.

datascience@berkeley offers a web-based learning environment that blends live, face-to-face classes with online coursework that can be accessed from anywhere with an Internet connection. The platform facilitates collaboration, meaningful discussion, and lifelong connections.

Columbia University offers an intensive Master of Information and Knowledge Strategy program that can be completed in 16 months. The Columbia program combines applicable professional learning with Ivy League academic rigor in a hybrid learning format. The dynamic program features interactive content and collaborative learning that foster relationship building with current and emerging data practitioners.

In addition to a bachelor’s degree, admission to the program requires two years of relevant professional experience. Graduates of the Columbia program have been employed as business process analysts, strategy and process improvement managers, and senior consultants for leading companies such as Abbott Laboratories, ADP, Comcast, Hewlett-Packard, Pfizer, and SapientNitro.

New York University has undertaken a tremendous initiative to emphasize data science across its schools and research centers. The university currently offers two on-campus programs. The MS in Data Science is a 36-credit program meant to be completed in four semesters, but can be compressed into three. A bachelor’s degree and a background in mathematics and computer science are required for admission. NYU also offers the related MS in Business Analytics through its highly ranked Stern School of Business. NYU programs typically come with a high price tag; however, as a number of media outlets have pointed out, the vigorous curriculum may be well worth the price of admission.

Northwestern offers two separate master’s level programs related to data science – the on-campus Master of Science in Analytics and the online Master of Science in Predictive Analytics. These 11-course programs can be completed in 15 months.

The on-campus program is more geared toward engineers, while the online program is more business oriented. Both promise to prepare graduates for work in the field.

Carnegie Mellon offers a Master of Information Systems Management with a Business Intelligence and Data Analytics concentration. This 36-credit, three-semester program is taught entirely at the university’s Pittsburgh campus and includes a summer internship. Admission requirements include a bachelor’s degree with courses in computer programming, statistics, and math. The Carnegie Mellon program aims to cross-train students in business process analysis and big data areas, including predictive modeling, segmentation analysis, mapping, analytical reporting, and data visualization.